A granular based semantics for fuzzy measures is introduced in which the measure of a set of propositions approximates the probability of the disjunction of these propositions. This approximation is derived from known probabilities across a granular partition of the set of possible worlds. This interpretation is then extended to allow for the case where there is uncertainty regarding the meanin...

This paper formulates multiobjective linear programming problems where each coefficient of the objective functions is expressed by a random fuzzy variable. Assuming that the decision maker concerns about the probability that each of the objective function values is smaller than or equal to a certain target value, the fuzzy goals of the decision maker for the probabilities are introduced. Then, ...

Focusing on the diversity, complexity and uncertainty of the third-party damage accident, the failure probability of third-party damage to urban gas pipeline was evaluated on the theory of analytic hierarchy process and fuzzy mathematics. The fault tree of third-party damage containing 56 basic events was built by hazard identification of third-party damage. The fuzzy evaluation of basic event ...

Estimation of the extent and spread of wildland fires is an important application of high spatial resolution multispectral images. This work addresses a fuzzy segmentation algorithm to map fire extent, active fire front, hot burn scar, and smoke regions based on a statistical model. The fuzzy results are useful data sources for integrated fire behavior and propagation models built using Dynamic...

This paper presents an adaptive fuzzy evidential reasoning approach for multi source based data fusion. A novel fuzzy evidence structure model is proposed under the assumption that each information source provides two types of evidence: probabilistic evidence (in terms of posteriori probabilities) and fuzzy evidence (in terms of fuzzy rules). A new information measure, called hybrid entropy, is...

A novel self-learning control algorithm for human-machine systems is presented. The designed controller is based on a probabilistic extension of recurrent fuzzy systems, which allows the consideration of non-deterministic information in addition to deterministic control signals. The behavior of the controller is adapted by varying the conditional probabilities of state switching, wherefore the ...

This paper is concerned with the problem of fault detection for discrete-time state-delay fuzzy systems. It is assumed that the output measurements are subject to random communication delay. The random communication delay is modeled as a finite state Markov process, and it is assumed that the transition probabilities are partially known. The problem addressed is the design of a delay-mode-depen...